Title :
Ellipsoidal low-demanding MPC schemes for uncertain polytopic discrete-time systems
Author :
Angeli, David ; Casavola, Alessandro ; Mosca, Edoardo
Author_Institution :
Dip. di Sistemi e Informatica, Univ. di Firenze, Italy
Abstract :
A model predictive control (MPC) method based on ellipsoidal calculus is described in order to address the control problems in the presence of state and input constraints for uncertain polytopic linear plants under persistent disturbances. In order to reduce the usually high numerical complexity and conservatism associated to polytopic robust MPC schemes the present approach consists of moving off-line most part of the computational burden and using closed-loop predictions. An example is also presented.
Keywords :
closed loop systems; discrete time systems; linear matrix inequalities; linear systems; predictive control; state feedback; uncertain systems; closed-loop predictions; discrete-time systems; ellipsoidal calculus; inner approximation criterion; linear matrix inequality; linear systems; model predictive control; polytopic systems; state-feedback; uncertain systems; Control systems; Predictive models; Robust control; Robustness; Stability; State-space methods; Uncertainty;
Conference_Titel :
Decision and Control, 2002, Proceedings of the 41st IEEE Conference on
Print_ISBN :
0-7803-7516-5
DOI :
10.1109/CDC.2002.1184300
